ECTS - Applied Time Series Analysis
Applied Time Series Analysis (ECON516) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Applied Time Series Analysis | ECON516 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Social Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Drill and Practice. |
| Course Lecturer(s) |
|
| Course Objectives | The aim of this course is to provide students the ability to understand, apply and interpret time series techniques used in applied economics literature. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Stationarity, unit root tests, unit root tests with structural break, concept of cointegration, cointegration tests, non-linear time series models. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Basic econometrics | Lecture Notes |
| 2 | Basic econometrics | Lecture Notes |
| 3 | Stationarity, weak dependency | Lecture Notes |
| 4 | Unit root tests | Lecture Notes |
| 5 | Unit root tests with structural break | Lecture Notes |
| 6 | Dominant property, common feature, cointegration | Lecture Notes |
| 7 | Cointegration tests: Engle-Granger | Lecture Notes |
| 8 | MIDTERM EXAM | |
| 9 | Time series filtering techniques | Lecture Notes |
| 10 | Dual Adjustment Approach | Lecture Notes |
| 11 | ARDL Models | Lecture Notes |
| 12 | NARDL Models | Lecture Notes |
| 13 | Application | Lecture Notes |
| 14 | FINAL EXAM |
Sources
| Course Book | 1. Gujarati D. N. (Çeviri: Şenesen Ü. ve Şenesen G. G.), 2012, Temel Ekonometri, Literatür Yayıncılık. |
|---|---|
| Other Sources | 2. Ekonometri ve Zaman Serisi Analizi ile ilgili Peryodik Yayınlar, Akademik Dergiler / Prediodicals and Academic Journals related to Econometrics and Time Series Analysis |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | 1 | 20 |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 50 |
| Toplam | 3 | 100 |
| Percentage of Semester Work | |
|---|---|
| Percentage of Final Work | 100 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | To compare main microeconomic theories, approaches and make a critical evaluation of each | X | ||||
| 2 | To compare main macroeconomic theories, approaches and make a critical evaluation of each | X | ||||
| 3 | To apply mathematical modeling | X | ||||
| 4 | To employ statistical and econometric tools in analyzing an economic phenomena | X | ||||
| 5 | To analyze the main economic indicators and comment on them | X | ||||
| 6 | To acquire theoretical knowledge through literature survey and derive empirically confirmable hypothesis | X | ||||
| 7 | To make a research design and carry it out within predetermined time frames | X | ||||
| 8 | To be able to develop new approaches for complex problems in applied economics and/or apply statistical/econometric tools to new areas/problems | X | ||||
| 9 | To formulate and present policy recommendations based on academic research | X | ||||
| 10 | To combine economic knowledge with other disciplines in order to solve problems requiring scientific expertise | X | ||||
| 11 | To use information technology effectively | X | ||||
| 12 | To continue learning and undertake advanced research independently | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 14 | 3 | 42 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | 1 | 21 | 21 |
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
| Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
| Total Workload | 125 | ||